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Practica 3 (Meyci Diaz, Gisselle Sanchez y Karen Larin).

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Image: ubuntu2204
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Kernel: R (system-wide)
dnorm (0,0, sqrt (0.2))
dnorm (0 ,0 ,1.0)
dnorm (0) # Cuando se omiten la media y la desviación se asumen como e y 1
dnorm (0,0, sqrt (5.0)) 
dnorm (0,-2, sqrt (0.5)) 
dnorm (-2,-2, sqrt (0.5))
[1] 0.8920621
[1] 0.3989423
[1] 0.3989423
[1] 0.1784124
[1] 0.01033349
[1] 0.5641896
x <-seq(-4 ,4 ,0.5) 
y <-dnorm(x)
plot(x,y, type="l")
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x <-seq(-3 ,3 ,0.1) 
y <-dnorm(x)
plot(x,y, type="l")
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x <-seq ( -3 ,3 ,0.1)
y <-dnorm (x,0,sqrt(0.2)) 
plot (x,y, type ="h")
Image in a Jupyter notebook
x <-seq ( -3 ,3 ,0.1)
y <-dnorm (x,0,sqrt(0.2)) 
plot (x,y, type ="b")
Image in a Jupyter notebook
x <-seq ( -3 ,3 ,0.1)
y <-dnorm (x,0,sqrt(0.2)) 
plot (x,y, type ="p")
Image in a Jupyter notebook
pnorm(0)
[1] 0.5
pnorm(15.7,15,0.5)
[1] 0.9192433
1-pnorm(15.7,15,0.5)
[1] 0.08075666
pnorm(15.7,15,0.5, lower.tail=FALSE)
[1] 0.08075666
pnorm(150,160,10)-pnorm(140,160,10)
[1] 0.1359051
dbinom (3,20,0.5)
dbinom(10,20,0.5)
dbinom (17,20,0.7)
dbinom (20,40,0.5)
[1] 0.001087189
[1] 0.1761971
[1] 0.07160367
[1] 0.1253707
x<-seq(0,40,1) 
y<-dbinom(x,40,0.5)
par(mfrow=c(1,2)) 
plot(x,y,type="h") 
plot(x,y,type="b")
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pbinom(20,40,0.5)
[1] 0.5626853
pbinom(6,15,0.25)-pbinom(2,15,0.25)
[1] 0.7072919
1-pbinom(5,15,0.25)
[1] 0.1483681